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arXiv:2405.09265 · IEEE International Conference on Quantum Computing and Engineering (QCE)

Quantum Computing Education for Computer Science Students: Bridging the Gap with Layered Learning and Intuitive Analogies

Anila Mjeda, Hazel Murray

Published Sep 15, 2024• 6 citations
arXivHTMLPDF

Abstract

Quantum computing presents a transformative potential for the world of computing. However, integrating this technology into the curriculum for computer science students who lack prior exposure to quantum mechanics and advanced mathematics remains a challenging task. This paper proposes a scaffolded learning approach aimed at equipping computer science students with essential quantum principles. By introducing foundational quantum concepts through relatable analogies and a layered learning approach based on classical computation, this approach seeks to bridge the gap between classical and quantum computing. This differs from previous approaches which build quantum computing fundamentals from the prerequisite of linear algebra and mathematics. The paper offers a considered set of intuitive analogies for foundation quantum concepts including entanglement, superposition, quantum data structures and quantum algorithms. These analogies coupled with a computing-based layered learning approach, lay the groundwork for a comprehensive teaching methodology tailored for undergraduate third level computer science students.

DOI
10.1109/qce60285.2024.20460

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Quantum computing presents a transformative potential for the world of computing. However, integrating this technology into the curriculum for computer science students who lack prior exposure to quantum mechanics and advanced mathematics remains a challenging task. This paper proposes a scaffolded learning approach aimed at equipping computer science students with essential quantum principles. By introducing foundational quantum concepts through relatable analogies and a layered learning approach based on classical computation, this approach seeks to bridge the gap between classical and quantum computing. This differs from previous approaches which build quantum computing fundamentals from the prerequisite of linear algebra and mathematics. The paper offers a considered set of intuitive analogies for foundation quantum concepts including entanglement, superposition, quantum data structures and quantum algorithms. These analogies coupled with a computing-based layered learning approach, lay the groundwork for a comprehensive teaching methodology tailored for undergraduate third level computer science students.
This chapter presents teachers and students with the fundamental concepts and principles of quantum computing in a fashion that is both for learners and educators. As quantum technologies are breaking into the lead roles in innovation, integrating quantum literacy into curriculum education is becoming increasingly essential. This chapter makes difficult concepts like qubits, superposition, entanglement, and quantum gates easy to understand and what makes classical and quantum computation distinct in easy-to-understand terms. It offers teachers effective methods for approaching quantum concepts through analogs, simulations, and hands-on devices like IBM’s Quantum Experience. For students, this chapter opens up inquiry by means of interactive and inquiry-based approaches, leading to increased understanding. Interdisciplinary education—physics, math, and computer science—is used as a starting point for the study of quantum mechanics and computing applications. It surveys current trends in quantum curriculum design and offers feasible case studies of effective quantum education initiatives in schools and universities. Problems of the absence of qualified teachers, lack of access to quantum materials, and learning inequalities are observed and accompanied by advice regarding scalable and inclusive methods of pedagogy.
Quantum computing poses unique challenges for computer science students due to the field's reliance on mathematical formalism, abstract physical concepts, and unfamiliar notation. While computer science students are typically proficient in algorithmic thinking and systems design, they often lack the background in quantum mechanics and linear algebra necessary to navigate the field's conceptual landscape. This mismatch can result in a form of disciplinary dissonance, a ‘Quantum Babel', where understanding breaks down due to divergent cognitive and notational frameworks. This paper proposes a layered, analogy-driven pedagogical framework that re-contextualizes quantum concepts using metaphors and structures familiar to CS learners. Grounded in cognitive load theory and analogical reasoning, the approach aims to reduce extraneous cognitive load through metaphorical scaffolding. For example, the quantum Hamiltonian is recast as an operating system task scheduler, facilitating intuitive understanding of time evolution and energy landscapes in quantum systems. We present a series of conceptual mappings and illustrative examples that enable learners to build quantum intuition using analogies drawn from classical computing domains such as signal processing, debugging, and resource scheduling. Our goal is to foster quantum intuition in learners without requiring a deep background in physics, supporting the emergence of a new generation of quantum-literate computer scientists. This work contributes to the growing field of quantum software engineering education and lays the foundation for empirically validated, cross-disciplinary teaching tools.
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Investments in quantum technologies, which are based on the effects of quantum mechanics, have escalated in recent years, with big players such as IBM, Google, and Microsoft engaging in the race for quantum supremacy. Some potential benefits of this cutting-edge technology include developing new drugs and materials through accurate molecule simulation, establishing more secure and reliable communication channels, and finding faster solutions for complex optimization problems. As quantum technologies evolve, however, the demand for new software, interfaces, and end-to-end systems to properly program and explore the advantages of quantum mechanics becomes paramount. This requires engineers, especially software engineers, and computer scientists, to have multidisciplinary knowledge and skills. Unfortunately, introductory quantum computing and technologies courses are mostly available in physics, and most engineering and computer science courses do not have modules on quantum physics, leading to a talent gap in the current job market. Therefore, this paper proposes a short teaching plan for introducing quantum computing to students with a more technology-based background, such as computer science and engineering students. This plan uses active learning methodologies, such as Challege-Based Teaching, to better engage these students and contextualize the many applications of this new technology. The initial teaching plan consists of a 3-hour seminar introducing the main quantum mechanics concepts and the technology applications, a 3-hour introduction to the math fundamentals and quantum logic gates, and a 3-hour handson workshop using the IBM Qiskit platform. Two versions of this plan were executed in two different moments: (1) a one-day event open to undergraduate students from different institutions and backgrounds, and (2) a 3-day internal training course for computer science and information technology management undergraduate students from our higher education institution. Data was collected during both events through online forms and interviews to measure the learning outcomes of the produced material and better understand the public interest in the field. The results identified key elements for better teaching quantum computing for computer scientists and engineers, providing guidelines for developing a more extensive and term-long teaching plan for undergraduate technology courses.
Quantum computing is an emerging field with growing implications across science and industry, making early educational exposure increasingly important. This paper examines how quantum computing concepts can be introduced into high-school STEM curricula within existing structures to enhance foundational learning in mathematics, computer science, and physics. We outline a modular integration strategy introducing key quantum ideas into standard courses, leveraging open-source educational resources to ensure global accessibility. Emphasis is placed on educational opportunity and equity: the approach is designed to be inclusive and to bridge current curricular gaps so that students worldwide can develop basic quantum literacy. Our analysis demonstrates that integrating quantum topics at the secondary level is feasible and can enrich STEM learning.
Quantum computing is a rapidly evolving field with transformative implications across domains such as cryptography, optimisation, materials science, drug discovery, and artificial intelligence. However, for quantum computing to reach its full potential, it must be accessible to researchers, engineers, and students from a wide variety of disciplinary backgrounds-many of whom may not have formal training in quantum mechanics or advanced physics. Analogies are powerful tools for bridging these gaps in understanding, particularly when introducing complex and unintuitive concepts like superposition, entanglement, or quantum interference. Yet analogies are often used spontaneously and without critical analysis, which can lead to misconceptions or inconsistent interpretations across fields. This tutorial introduces a structured approach-structure mapping-for evaluating, refining, and co-creating analogies for quantum education. Through collaborative activities, participants will learn to identify where analogies succeed or fail, explore analogies from other disciplines, and gain tools for making quantum ideas more accessible to non-experts. This is particularly valuable for postgraduate educators, curriculum designers, outreach specialists, and researchers working in interdisciplinary quantum projects. By the end of the tutorial, participants will have gained practical skills in analogy evaluation, a toolkit for effective communication of quantum concepts, and a shared vocabulary to enhance interdisciplinary collaboration.